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No-boundary thinking in bioinformatics research

Overview of attention for article published in BioData Mining, November 2013
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (87th percentile)
  • Good Attention Score compared to outputs of the same age and source (69th percentile)

Mentioned by

twitter
18 tweeters

Citations

dimensions_citation
6 Dimensions

Readers on

mendeley
59 Mendeley
citeulike
3 CiteULike
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Title
No-boundary thinking in bioinformatics research
Published in
BioData Mining, November 2013
DOI 10.1186/1756-0381-6-19
Pubmed ID
Authors

Xiuzhen Huang, Barry Bruce, Alison Buchan, Clare Bates Congdon, Carole L Cramer, Steven F Jennings, Hongmei Jiang, Zenglu Li, Gail McClure, Rick McMullen, Jason H Moore, Bindu Nanduri, Joan Peckham, Andy Perkins, Shawn W Polson, Bhanu Rekepalli, Saeed Salem, Jennifer Specker, Donald Wunsch, Donghai Xiong, Shuzhong Zhang, Zhongming Zhao

Abstract

Currently there are definitions from many agencies and research societies defining "bioinformatics" as deriving knowledge from computational analysis of large volumes of biological and biomedical data. Should this be the bioinformatics research focus? We will discuss this issue in this review article. We would like to promote the idea of supporting human-infrastructure (HI) with no-boundary thinking (NT) in bioinformatics (HINT).

Twitter Demographics

The data shown below were collected from the profiles of 18 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 59 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 5 8%
United Kingdom 1 2%
Indonesia 1 2%
India 1 2%
Unknown 51 86%

Demographic breakdown

Readers by professional status Count As %
Researcher 13 22%
Student > Ph. D. Student 12 20%
Professor > Associate Professor 6 10%
Other 6 10%
Student > Master 5 8%
Other 16 27%
Unknown 1 2%
Readers by discipline Count As %
Agricultural and Biological Sciences 15 25%
Biochemistry, Genetics and Molecular Biology 10 17%
Computer Science 8 14%
Medicine and Dentistry 7 12%
Engineering 4 7%
Other 10 17%
Unknown 5 8%

Attention Score in Context

This research output has an Altmetric Attention Score of 12. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 20 February 2015.
All research outputs
#1,784,126
of 16,040,711 outputs
Outputs from BioData Mining
#54
of 254 outputs
Outputs of similar age
#22,889
of 190,754 outputs
Outputs of similar age from BioData Mining
#7
of 23 outputs
Altmetric has tracked 16,040,711 research outputs across all sources so far. Compared to these this one has done well and is in the 88th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 254 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.5. This one has done well, scoring higher than 78% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 190,754 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 87% of its contemporaries.
We're also able to compare this research output to 23 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 69% of its contemporaries.